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Synergies Between Robots and Games Gita Sukthankar gitars@eecs.ucf.edu Motivation UT3 Travian http://images.google.com/q=multi-robot+systems Robotics: Strengths n Better formal representations of the physical world n More autonomous


  1. Synergies Between Robots and Games Gita Sukthankar gitars@eecs.ucf.edu

  2. Motivation UT3 Travian http://images.google.com/q=multi-robot+systems

  3. Robotics: Strengths n Better formal representations of the physical world n More autonomous planning rather than reliance on scripting n Belief in the power of integrating machine learning algorithms Robotics on CFP at the AAAI Conference on AI and Interactive Digital Entertainment (2012 and 2013)

  4. Games: Human-Centered Design Making experiences fun rather than frustrating Dynamic difficulty adjustment

  5. Games tell Stories The power of narrative and character development

  6. Games: Intuitive Control Dedicated but impatient user base seeks fast control

  7. Games: Modeling Group Behavior Studying individual communication and trade patterns reveals hidden social structures

  8. Predic'ng ¡ ¡Guild ¡ ¡Memb mbership ¡ ¡in ¡ ¡Massively ¡ ¡Mul'player ¡ ¡Online ¡ ¡Game mes Hamidreza ¡Alvari 1 , ¡Kiran ¡Lakkaraju 2 ¡, ¡Gita ¡Sukthankar 1 ¡, ¡and ¡Jon ¡Whetzel 2 ¡ ¡ 1 ¡ University ¡of ¡Central ¡Florida, ¡Orlando, ¡Florida 2 ¡Sandia ¡Na'onal ¡Labs, ¡Albuquerque, ¡New ¡Mexico Join ¡ ? ¡ Leave ¡ Social ¡Ties ¡ Switch ¡ Rela1ve ¡ Contribu1on ¡ No ¡Ac1on ¡ Exis1ng ¡ Skill ¡ guild ¡ Homophily ¡ informa1on ¡ Guild ¡predic1on ¡is ¡more ¡accurate ¡when ¡seeded ¡with ¡a ¡few ¡highly ¡ central ¡members ¡rather ¡than ¡larger ¡numbers ¡of ¡less ¡influen1al. ¡

  9. Future: Robots, Agents, and People n Future: scaling up not only the robots but the number of people dealing with the same robots. n Less focus on point-to-point interaction n Social network and modeling techniques developed for game analytics may be helpful in understanding the holistic system operation. n Call to action: ¨ More public datasets ¨ More shared testbeds for running experiments

  10. Intelligent Agents Lab http://ial.eecs.ucf.edu/ Ph.D. Students n Hamidreza Alvari n Rahmatollah Beheshti n Erfan Davami n Alireza Hajibagheri n Astrid Jackson Alumni Bulent Tastan (Amazon), Ken Laviers (SRSU), JT Folsom-Kovarik (SoarTech), Fahad Shah (Microsoft), Bennie Lewis (Lockheed Martin), Mahsa Maghami (Microsoft), Yuan Chang (Google), Xi Wang (Sonobi) Sponsors: AFOSR YIP, NSF CAREER, DARPA CSSP

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